A Practical Tutorial on Deep Learning for Text and Data Integration


Luciano Barbosa (Cin/UFPE)


Recently, deep learning (DL) techniques have obtained state-of-the-art results in a great variety of text-related problems as, for instance, named entity recognition tagging, sentence classification and machine translation.  In this tutorial, we aim to introduce the main DL approaches and their usage for  text mining and data integration. For that, we will provide practical examples of deep networks using an easy-to-use Python tool: Keras.  At the end of this tutorial, you should be able to build your own deep networks for your specific text-related problems using Keras.


Luciano Barbosa  is Assistant Professor in the Computer Science Department at Universidade Federal de Pernambuco. Previously, he worked as Research Scientist in two research labs: IBM Research – Brazil and AT&T Research Labs – USA. He obtained his Ph.D. in Computing at University of Utah, and his B.S. and M.S. in Computer Science at Universidade Federal de Pernambuco.  His research interests include web mining, text mining and data analytics..